Mixed selectivity coding of sensory and motor social signals in the thalamus of a weakly electric fish
Bibliographic record
Abstract
Abstract Recent studies have shown that high-level neural activity often exhibits mixed selectivity to multivariate signals. How such representations arise and how they modulate natural behavior is poorly understood. The social behavior of weakly electric fish is relatively low-dimensional and easily reproduced in the laboratory. Here we show how electrosensory signals related to courtship and rivalry in Apteronotus leptorhynchus are represented in the preglomerular nucleus, the thalamic region exclusively connecting the midbrain with the pallium. We show that preglomerular cells convert their midbrain inputs into a mixed selectivity code that includes corollary discharge of outgoing communication signals. We discuss how the preglomerular pallial targets might use these inputs to control social behavior and determine dominance in male-male competition and female mate selection during courtship. Our results showcase the potential of the electrocommunication system as an accessible model for studying the neural substrates of social behavior and principles of multi-dimensional neural representation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".